Prediction of RTK-GNSS performance in urban environments using a 3D model and continuous LoS method
dc.contributor.author | Furukawa, R. | |
dc.contributor.author | Kubo, N. | |
dc.contributor.author | El-Mowafy, Ahmed | |
dc.date.accessioned | 2020-06-22T10:24:30Z | |
dc.date.available | 2020-06-22T10:24:30Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Furukawa, R. and Kubo, N. and El-Mowafy, A. 2020. Prediction of RTK-GNSS performance in urban environments using a 3D model and continuous LoS method. In Proceedings of the 2020 International Technical Meeting of The Institute of Navigation, ION ITM 2020, 21-24 January 2020, San Diego, USA. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/79702 | |
dc.identifier.doi | 10.33012/2020.17176 | |
dc.description.abstract |
© 2020 ION 2020 International Technical Meeting Proceedings. All rights reserved. To utilize RTK-GNSS in urban areas, it is important to predict areas in which it can be used. The performance of RTK-GNSS depends on the geometry and number of visible satellites and signal quality. These parameters can potentially be predicted using simulations that consider the relative geometry between the receiver and surrounding objects. In this study, we first verified whether the GNSS signal quality can be correctly predicted using 3D models of buildings and measurement data. Subsequently, we verified whether the FIX status of RTK can be correctly predicted. The results show that the number of the measured and predicted satellites that have good signal quality was in agreement at least 87.8% of the time. We assessed and categorized the RTK-GNSS fixing status using the number of usable satellites. A comparison of the RTK fixed status estimation, using the actual measurements and those from the simulation, agreed within 83.9% of the total. | |
dc.title | Prediction of RTK-GNSS performance in urban environments using a 3D model and continuous LoS method | |
dc.type | Conference Paper | |
dcterms.source.startPage | 763 | |
dcterms.source.endPage | 771 | |
dcterms.source.title | ION 2020 International Technical Meeting Proceedings | |
dcterms.source.isbn | 0936406240 | |
dcterms.source.isbn | 9780936406244 | |
dc.date.updated | 2020-06-22T10:24:30Z | |
curtin.department | School of Earth and Planetary Sciences (EPS) | |
curtin.accessStatus | Fulltext not available | |
curtin.faculty | Faculty of Science and Engineering | |
curtin.contributor.orcid | El-Mowafy, Ahmed [0000-0001-7060-4123] | |
curtin.contributor.scopusauthorid | El-Mowafy, Ahmed [7004059531] |